FM / methods

/usr/local/lib64/python3.6/site-packages/pandas/tests/frame/methods/

/usr/local/lib64/python3.6/site-packages/pandas/tests/frame/methods

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
test_align.py	10339	0644	edit dl rm
test_append.py	7399	0644	edit dl rm
test_asfreq.py	1970	0644	edit dl rm
test_asof.py	5767	0644	edit dl rm
test_assign.py	2982	0644	edit dl rm
test_astype.py	21027	0644	edit dl rm
test_at_time.py	3205	0644	edit dl rm
test_between_time.py	3675	0644	edit dl rm
test_clip.py	6028	0644	edit dl rm
test_combine.py	1359	0644	edit dl rm
test_combine_first.py	12748	0644	edit dl rm
test_compare.py	6158	0644	edit dl rm
test_count.py	1068	0644	edit dl rm
test_cov_corr.py	11888	0644	edit dl rm
test_describe.py	12492	0644	edit dl rm
test_diff.py	7374	0644	edit dl rm
test_drop.py	15662	0644	edit dl rm
test_droplevel.py	855	0644	edit dl rm
test_drop_duplicates.py	13387	0644	edit dl rm
test_duplicated.py	3191	0644	edit dl rm
test_explode.py	5294	0644	edit dl rm
test_filter.py	4933	0644	edit dl rm
test_first_and_last.py	1803	0644	edit dl rm
test_head_tail.py	1194	0644	edit dl rm
test_interpolate.py	11816	0644	edit dl rm
test_isin.py	7324	0644	edit dl rm
test_nlargest.py	6731	0644	edit dl rm
test_pct_change.py	3436	0644	edit dl rm
test_pop.py	1226	0644	edit dl rm
test_quantile.py	18028	0644	edit dl rm
test_rank.py	11377	0644	edit dl rm
test_reindex_like.py	1187	0644	edit dl rm
test_rename.py	12543	0644	edit dl rm
test_rename_axis.py	4074	0644	edit dl rm
test_replace.py	59230	0644	edit dl rm
test_reset_index.py	12506	0644	edit dl rm
test_round.py	7916	0644	edit dl rm
test_select_dtypes.py	12104	0644	edit dl rm
test_set_index.py	19571	0644	edit dl rm
test_shift.py	10324	0644	edit dl rm
test_sort_index.py	25678	0644	edit dl rm
test_sort_values.py	25358	0644	edit dl rm
test_to_dict.py	9989	0644	edit dl rm
test_to_period.py	984	0644	edit dl rm
test_to_records.py	13981	0644	edit dl rm
test_to_timestamp.py	4020	0644	edit dl rm
test_transpose.py	2426	0644	edit dl rm
test_truncate.py	4180	0644	edit dl rm
test_tz_convert.py	3415	0644	edit dl rm
test_tz_localize.py	666	0644	edit dl rm
test_update.py	4259	0644	edit dl rm
test_value_counts.py	2631	0644	edit dl rm
__init__.py	229	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pandas/tests/frame/methods/test_value_counts.py (2631B)

import numpy as np

import pandas as pd
import pandas._testing as tm

def test_data_frame_value_counts_unsorted():
    df = pd.DataFrame(
        {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
        index=["falcon", "dog", "cat", "ant"],
    )

result = df.value_counts(sort=False)
    expected = pd.Series(
        data=[1, 2, 1],
        index=pd.MultiIndex.from_arrays(
            [(2, 4, 6), (2, 0, 0)], names=["num_legs", "num_wings"]
        ),
    )

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_ascending():
    df = pd.DataFrame(
        {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
        index=["falcon", "dog", "cat", "ant"],
    )

result = df.value_counts(ascending=True)
    expected = pd.Series(
        data=[1, 1, 2],
        index=pd.MultiIndex.from_arrays(
            [(2, 6, 4), (2, 0, 0)], names=["num_legs", "num_wings"]
        ),
    )

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_default():
    df = pd.DataFrame(
        {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
        index=["falcon", "dog", "cat", "ant"],
    )

result = df.value_counts()
    expected = pd.Series(
        data=[2, 1, 1],
        index=pd.MultiIndex.from_arrays(
            [(4, 6, 2), (0, 0, 2)], names=["num_legs", "num_wings"]
        ),
    )

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_normalize():
    df = pd.DataFrame(
        {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]},
        index=["falcon", "dog", "cat", "ant"],
    )

result = df.value_counts(normalize=True)
    expected = pd.Series(
        data=[0.5, 0.25, 0.25],
        index=pd.MultiIndex.from_arrays(
            [(4, 6, 2), (0, 0, 2)], names=["num_legs", "num_wings"]
        ),
    )

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_single_col_default():
    df = pd.DataFrame({"num_legs": [2, 4, 4, 6]})

result = df.value_counts()
    expected = pd.Series(
        data=[2, 1, 1],
        index=pd.MultiIndex.from_arrays([[4, 6, 2]], names=["num_legs"]),
    )

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_empty():
    df_no_cols = pd.DataFrame()

result = df_no_cols.value_counts()
    expected = pd.Series([], dtype=np.int64)

tm.assert_series_equal(result, expected)

def test_data_frame_value_counts_empty_normalize():
    df_no_cols = pd.DataFrame()

result = df_no_cols.value_counts(normalize=True)
    expected = pd.Series([], dtype=np.float64)

tm.assert_series_equal(result, expected)

import numpy as np import pandas as pd import pandas._testing as tm def test_data_frame_value_counts_unsorted(): df = pd.DataFrame( {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]}, index=["falcon", "dog", "cat", "ant"], ) result = df.value_counts(sort=False) expected = pd.Series( data=[1, 2, 1], index=pd.MultiIndex.from_arrays( [(2, 4, 6), (2, 0, 0)], names=["num_legs", "num_wings"] ), ) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_ascending(): df = pd.DataFrame( {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]}, index=["falcon", "dog", "cat", "ant"], ) result = df.value_counts(ascending=True) expected = pd.Series( data=[1, 1, 2], index=pd.MultiIndex.from_arrays( [(2, 6, 4), (2, 0, 0)], names=["num_legs", "num_wings"] ), ) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_default(): df = pd.DataFrame( {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]}, index=["falcon", "dog", "cat", "ant"], ) result = df.value_counts() expected = pd.Series( data=[2, 1, 1], index=pd.MultiIndex.from_arrays( [(4, 6, 2), (0, 0, 2)], names=["num_legs", "num_wings"] ), ) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_normalize(): df = pd.DataFrame( {"num_legs": [2, 4, 4, 6], "num_wings": [2, 0, 0, 0]}, index=["falcon", "dog", "cat", "ant"], ) result = df.value_counts(normalize=True) expected = pd.Series( data=[0.5, 0.25, 0.25], index=pd.MultiIndex.from_arrays( [(4, 6, 2), (0, 0, 2)], names=["num_legs", "num_wings"] ), ) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_single_col_default(): df = pd.DataFrame({"num_legs": [2, 4, 4, 6]}) result = df.value_counts() expected = pd.Series( data=[2, 1, 1], index=pd.MultiIndex.from_arrays([[4, 6, 2]], names=["num_legs"]), ) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_empty(): df_no_cols = pd.DataFrame() result = df_no_cols.value_counts() expected = pd.Series([], dtype=np.int64) tm.assert_series_equal(result, expected) def test_data_frame_value_counts_empty_normalize(): df_no_cols = pd.DataFrame() result = df_no_cols.value_counts(normalize=True) expected = pd.Series([], dtype=np.float64) tm.assert_series_equal(result, expected)